





"""simple docstring"""





import doctest
from collections import deque

import numpy as np





class      snake_case						:

      def __init__(     self  :int		):
       __SCREAMING_SNAKE_CASE					:     int   				=			[2, 1, 2, -1]
       __SCREAMING_SNAKE_CASE					:     List[Any]   				=			[1, 2, 3, 4]



      def 		SCREAMING_SNAKE_CASE_     (     self  :List[Any]		):
       __SCREAMING_SNAKE_CASE					:     Dict   				=			len(self.first_signal		)
       __SCREAMING_SNAKE_CASE					:     str   				=			len(self.second_signal		)

       __SCREAMING_SNAKE_CASE					:     int   				=			max(__UpperCamelCase		,				__UpperCamelCase		)

       # create a zero matrix of max_length x max_length
       __SCREAMING_SNAKE_CASE					:     List[str]   				=			[[0] * max_length for i in range(__UpperCamelCase		)]

       # fills the smaller signal with zeros to make both signals of same length
       if length_first_signal < length_second_signal:
        self.first_signal += [0] * (max_length - length_first_signal)
       elif length_first_signal > length_second_signal:
        self.second_signal += [0] * (max_length - length_second_signal)
       for i in range(__UpperCamelCase		):
        __SCREAMING_SNAKE_CASE					:     str   				=			deque(self.second_signal		)
        rotated_signal.rotate(__UpperCamelCase		)
        for j, item in enumerate(__UpperCamelCase		):
         matrix[i][j] += item

        # multiply the matrix with the first signal
       __SCREAMING_SNAKE_CASE					:     Optional[int]   				=			np.matmul(np.transpose(__UpperCamelCase		)		,				np.transpose(self.first_signal		)		)

       # rounding-off to two decimal places
       return [round(__UpperCamelCase		,				2		) for i in final_signal]


if __name__ == "__main__":
    doctest.testmod()



"""simple docstring"""



from ....configuration_utils import PretrainedConfig
from ....utils import logging


a       :						Dict       		=		logging.get_logger(__name__)

# TODO: upload to AWS
a       :						Tuple       		=		{
    '''yjernite/retribert-base-uncased''': (
        '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/config.json'''
    ),
}




class 		a_    (			_UpperCAmelCase						):
    a   :					int			     =					'retribert'







    def __init__(      self      :							Optional[Any]  ,       __UpperCamelCase      :							Optional[Any]=3_05_22  ,       __UpperCamelCase      :							int=7_68  ,       __UpperCamelCase      :							Any=8  ,       __UpperCamelCase      :							Dict=12  ,       __UpperCamelCase      :							List[Any]=30_72  ,       __UpperCamelCase      :							List[Any]="gelu"  ,       __UpperCamelCase      :							Optional[int]=0.1  ,       __UpperCamelCase      :							int=0.1  ,       __UpperCamelCase      :							Union[str, Any]=5_12  ,       __UpperCamelCase      :							Dict=2  ,       __UpperCamelCase      :							Tuple=0.0_2  ,       __UpperCamelCase      :							List[str]=1e-12  ,       __UpperCamelCase      :							int=True  ,       __UpperCamelCase      :							str=1_28  ,       __UpperCamelCase      :							Union[str, Any]=0  ,       **__UpperCamelCase      :							Any  ,       )		->List[Any]:






        '''simple docstring'''






        super().__init__(pad_token_id=__UpperCamelCase  ,       **__UpperCamelCase  )

        _UpperCAmelCase        = vocab_size
        _UpperCAmelCase        = hidden_size
        _UpperCAmelCase        = num_hidden_layers
        _UpperCAmelCase        = num_attention_heads
        _UpperCAmelCase        = hidden_act
        _UpperCAmelCase        = intermediate_size
        _UpperCAmelCase        = hidden_dropout_prob
        _UpperCAmelCase        = attention_probs_dropout_prob
        _UpperCAmelCase        = max_position_embeddings
        _UpperCAmelCase        = type_vocab_size
        _UpperCAmelCase        = initializer_range
        _UpperCAmelCase        = layer_norm_eps
        _UpperCAmelCase        = share_encoders
        _UpperCAmelCase        = projection_dim